Bioinformatic study in profiling the gut microbial community of giant panda (Ailuropoda melanoleuca) from metagenomic shotgun data

Abstract

As a miraculous member in mammals, giant panda is a strict vegetarian while its gastrointestinal tract possesses a typical digestive system of carnivores. Although it has evolved special pseudo-thumbs, and developed the teeth, mandible, skull and chewing muscles well to adapt the favorite food bamboo in morphology, no cellulolytic enzymes have been identified in the panda’s genome. Therefore, the gut microbiota in the giant panda is hypothesized to play the crucial role in lignocellulosic digestion. Besides the diet, the gut microbial community also interacts with the host health and aging in a dynamic ecosystem model, thus engages the unprecedented efforts in research and conservation of giant panda. As the result, deep shotgun metagenomic datasets were generated for the analysis of gut microbiota in giant panda. In Chapter 2 and 3 of this thesis, the quality of metagenomic assembly was compared between sequencing platforms and optimized with putative influencing factors, such as read length, library length and max k-mer length. The ultrahigh throughput Illumina sequencing platform was shown to provide more complete profiling with a comparable error rate, which was considered as more appropriate for metagenomic study despite of its inherent limitation in read length. On the other hand, numerous attempts to improve assembly quality with the adjustments of multiple putative influencing factors were performed for the optimization of both laboratory and computational designs. These two chapters provided computational analysis of the metagenomic assembly of the giant panda gut microbial community, to facilitate the metagenomic profiling more comprehensive with high accuracy. In Chapter 4, the descriptive metagenomic analysis revealed the giant panda gut microbiota was significantly distinguished from all other carnivores and herbivores. The microbial compositions vary remarkably during the growth state changing from juvenile to adult, and aging as well. Furthermore, the dramatic decrease of cellulolytic Clostridium species was discovered during the aging process in the gut of world’s oldest panda, and the booming of a virus family Myoviridae was found predominantly in the geriatric panda group. In Chapter 5, functional metagenomics not only discovered substantial evidence of cellulose, hemicellulose and lignin related protein coding genes in metagenomic data, but also identified the extreme low abundance of cellulose-related glycoside hydrolase enzymes in giant panda gut, which might reflect the low digestibility of the lignocellulosic diet. In addition, the putative cellulolytic population genome was recovered through pure bioinformatic computation, demonstrating the research value of assembling individual uncultivated bacterial genome from complex community metagenomic dataset. The success in reconstruction of uncultured experimental bacteria thus will hopefully spur more interaction among biologists and bioinformaticians in future metagenomic studies. This is the first study of deep shotgun metagenomic sequencing for the gut microbiota in giant panda, where comprehensive profiling for the microbial community structure and function is successfully constructed. The profiling results could provide guide for further experimental diet, health, and aging studies in giant panda.